分区模式下环形2-RGV系统优化调度研究  

Optimal Scheduling of 2-RGV System with Circular Rail in a Zone Partition Operating Mode

作　　者：陈华[1] 王天浩 王新平[1] 石梦华 CHEN Hua;WANG Tianhao;WANG Xinping;SHI Menghua(School of Management,Xi′an University of Science and Technology,Xi′an,Shaanxi 710054,China)

机构地区：[1]西安科技大学管理学院,陕西西安710054

出　　处：《工业工程与管理》2022年第1期74-82,共9页Industrial Engineering and Management

基　　金：国家自然科学基金面上项目(71673220);陕西省教育厅科学研究计划项目(18JK0494);西安科技大学博士(后)启动金项目(2017QDJ055);西安科技大学哲学社会科学繁荣计划重点项目(2018SZ02);教育部人文社会科学项目(19YJC630069)

摘　　要：环形穿梭车(rail guided vehicle,RGV)系统在自动化立体仓库(automated storage and retrieval system,AS/RS)中得到广泛应用,但在应用过程中易发生RGV碰撞或无效等待。针对环形2-RGV系统优化调度存在的问题,采用分区法进行研究,以最小化物料出库总时间为目标,提出了分区约束、碰撞避免约束以及RGV与堆垛机协同作业等约束,建立了分区模式下环形2-RGV优化调度问题的混合整数线性规划模型。设计了一种混合自适应遗传算法(hybrid adaptive genetic algorithm,HAGA)求解该问题,并给出了问题的下界。在算例试验中,将HAGA的求解结果与下界和CPLEX求解结果对比,不同规模算例下出库时间的平均偏差分别为3.4%和0.1%,且HAGA求解耗时均少于8 min;与变邻域搜索算法对比,HAGA在所有算例上的平均出库时间节约了8.3%,证明所提出HAGA能够快速有效地求解该问题。The rail guide vehicle(RGV)system with circular rail is widely used in the automatic storage and retrieval system(AS/RS).However,in the application,there are problems such as collisions between RGVs and extra RGV waiting time.This paper introduced a partitioning method to solve the scheduling problem of the 2-RGV system with circular rail.The objective was to minimize the total retrieval time.This paper proposed partition constraints,collision avoidance constraints,and collaborative operation constraints of RGV and stackers.A mixed integer linear programming model of the scheduling problem was established in a zone partition operating mode.A hybrid adaptive genetic algorithm(HAGA)was designed to solve the problem and a lower bound of the problem was given.In the numerical experiments,the results of HAGA were firstly compared with both the lower bound and the calculation results of CPLEX.The computational results show that the average deviations are3.4%and 0.1%for different experiment sizes,and the computation times of HAGA on all instances are less than 8 minutes.The results of HAGA are then compared with the results of variable neighborhood search algorithm;the average retrieval time of all instances obtained by HAGA is improved by 8.3%.The computational results show that the proposed HAGA can solve this problem efficiently.

关 键 词：环形穿梭车调度 分区模式 混合整数线性规划模型 混合自适应遗传算法 

分 类 号：TH24[机械工程—机械制造及自动化]